標(biāo)題: Titlebook: Applied Intelligence and Informatics; Second International Mufti Mahmud,Cosimo Ieracitano,Francesco Carlo Mor Conference proceedings 2022 T [打印本頁] 作者: 搖尾乞憐 時(shí)間: 2025-3-21 19:02
書目名稱Applied Intelligence and Informatics影響因子(影響力)
書目名稱Applied Intelligence and Informatics影響因子(影響力)學(xué)科排名
書目名稱Applied Intelligence and Informatics網(wǎng)絡(luò)公開度
書目名稱Applied Intelligence and Informatics網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Applied Intelligence and Informatics被引頻次
書目名稱Applied Intelligence and Informatics被引頻次學(xué)科排名
書目名稱Applied Intelligence and Informatics年度引用
書目名稱Applied Intelligence and Informatics年度引用學(xué)科排名
書目名稱Applied Intelligence and Informatics讀者反饋
書目名稱Applied Intelligence and Informatics讀者反饋學(xué)科排名
作者: PLIC 時(shí)間: 2025-3-21 22:53 作者: 木訥 時(shí)間: 2025-3-22 01:29
An Indirect Approach to?Forecast Produced Power on?Photovoltaic Plants Under Uneven Shading Condition of a virtual irradiance sensing methodology and a neural network forecasting system. The strength of this approach resides in its capability to support forecasting in presence of distributed shading patterns along the PV plant, without the necessity of external pyranometers or a complex data acqui作者: 音的強(qiáng)弱 時(shí)間: 2025-3-22 05:34 作者: 華而不實(shí) 時(shí)間: 2025-3-22 09:59 作者: 你正派 時(shí)間: 2025-3-22 16:28
Tackling the?Linear Sum Assignment Problem with?Graph Neural Networksunications. In general, solving assignment problems to optimality is computationally infeasible even for contexts of small dimensionality, and so heuristic algorithms are often employed to find near-optimal solutions. The handcrafting of a heuristic usually requires expert-knowledge to exploit the p作者: 的染料 時(shí)間: 2025-3-22 20:35
A Nonparametric Model for?Forecasting Life Expectancy at?Birth Using Gaussian Processs a practical and powerful approach. To plan for economic services for any nation, projections of future Life Expectancy (LE) are required. In our research, we have proposed a model to forecast LE using GPR up to 2040. Initially, we sub-categorized countries into four sections based on income level.作者: 草率男 時(shí)間: 2025-3-23 00:38 作者: 緊張過度 時(shí)間: 2025-3-23 03:11
Explainable Deep Learning for?Alzheimer Disease Classification and?Localisationlities. The accurate diagnosis of Alzheimer’s disease at an early stage is very crucial for patient care and conducting future treatment. Deep learning can help to reach the diagnosis: for this reason we propose a method aimed to distinguish and properly classify four Alzheimer disease’s stages. Two作者: Medicaid 時(shí)間: 2025-3-23 07:40
ML-Based Radiomics Analysis for?Breast Cancer Classification in?DCE-MRIor breast lesions characterization is widely used in the clinical practice, physician grading performance is still not optimal, showing a specificity of about 72%. In this work Radiomics was used to analyze a dataset acquired with two different protocols in order to train Machine-Learning algorithms作者: Ondines-curse 時(shí)間: 2025-3-23 10:17 作者: abreast 時(shí)間: 2025-3-23 15:38
A Novel Fuzzy Semi-supervised Learning Approach for?the?Classification of?Colorectal Cancer (FSSL-CR CRC has become the second most prevailing sort of cancer in the human race. But CRC until now remains linked to a poor diagnosis in patients with severe illness. The concern for early detection drew researchers’ consciousness to a variety of machine learning-based methods. Semi-Supervised Learning 作者: 不足的東西 時(shí)間: 2025-3-23 18:10
Machine Learning Models to?Analyze the?Effect of?Drugs on?Neonatal-ICU Length of?Stayictive models will help to indicate the seriousness of the patients and assist the doctors in taking immediate actions. The Medical Information Mart for Intensive Care III (MIMIC-III) dataset is used in this research. The medicines medicated in critical newborn children were detected, and how the dr作者: 嘮叨 時(shí)間: 2025-3-24 00:53 作者: 莎草 時(shí)間: 2025-3-24 05:46
Ensemble Classifiers for a 4-Way Classification of Alzheimer’s Diseaseto its ability to rapid learning of end-to-end models accurately using compound data. Recent years have seen an extensive application of Deep Learning (DL) models in solving the 4-way classification of Alzheimer’s Disease (AD) and achieved good results too. However, traditional machine learning clas作者: 飲料 時(shí)間: 2025-3-24 08:49 作者: NOCT 時(shí)間: 2025-3-24 14:38
Communications in Computer and Information Sciencehttp://image.papertrans.cn/a/image/159886.jpg作者: 有發(fā)明天才 時(shí)間: 2025-3-24 14:51
https://doi.org/10.1007/978-3-031-24801-6Computer Science; Informatics; Conference Proceedings; Research; Applications作者: electrolyte 時(shí)間: 2025-3-24 20:33
978-3-031-24800-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: AND 時(shí)間: 2025-3-25 02:40
,Strategie und Gesch?ftsmodell,and analyses the human activity of continuous frame or video sequence data from various sensors. Human activity such as walking, standing, running, sitting, jogging, interaction and so on is a good representation. The human activity contains such inter-class differences, intra-class similarities and作者: 背叛者 時(shí)間: 2025-3-25 05:46 作者: entreat 時(shí)間: 2025-3-25 08:12
Innovation und Entrepreneurship,n of a virtual irradiance sensing methodology and a neural network forecasting system. The strength of this approach resides in its capability to support forecasting in presence of distributed shading patterns along the PV plant, without the necessity of external pyranometers or a complex data acqui作者: 按時(shí)間順序 時(shí)間: 2025-3-25 15:23
https://doi.org/10.1007/978-3-658-26117-7many application fields, especially in the context of Body Sensor Networks (BSNs) where features of interest have to be extracted from the data collected by wearable sensors. In the last few years, the ever increasing size of the collected data, as well as low-power and high-speed constraints, have 作者: blister 時(shí)間: 2025-3-25 18:14 作者: Fierce 時(shí)間: 2025-3-25 20:22 作者: 芭蕾舞女演員 時(shí)間: 2025-3-26 02:05 作者: 錯(cuò)誤 時(shí)間: 2025-3-26 05:44 作者: 礦石 時(shí)間: 2025-3-26 11:23 作者: 內(nèi)閣 時(shí)間: 2025-3-26 12:51 作者: Texture 時(shí)間: 2025-3-26 17:06 作者: sleep-spindles 時(shí)間: 2025-3-26 23:25 作者: 調(diào)整 時(shí)間: 2025-3-27 03:22
Nezameddin Faghih,Mohammad Reza Zaliictive models will help to indicate the seriousness of the patients and assist the doctors in taking immediate actions. The Medical Information Mart for Intensive Care III (MIMIC-III) dataset is used in this research. The medicines medicated in critical newborn children were detected, and how the dr作者: Minuet 時(shí)間: 2025-3-27 09:15 作者: asthma 時(shí)間: 2025-3-27 11:33
Shahamak Rezaei,Victoria Hill,Yipeng Liuto its ability to rapid learning of end-to-end models accurately using compound data. Recent years have seen an extensive application of Deep Learning (DL) models in solving the 4-way classification of Alzheimer’s Disease (AD) and achieved good results too. However, traditional machine learning clas作者: Sad570 時(shí)間: 2025-3-27 13:46
Ali Davari,Amer Dehghan Najmabadiasurement of the Crown to Rump Length (CRL), it is a crucial scan as it informs obstetric practitioners of the optimal timing for any necessary interventions at the earliest point. Inter-observer variation creates problems for Obstetric Practitioners as any variation in the measurement of the CRL ca作者: slow-wave-sleep 時(shí)間: 2025-3-27 21:42
Applied Intelligence and Informatics978-3-031-24801-6Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: 中世紀(jì) 時(shí)間: 2025-3-27 22:15 作者: hegemony 時(shí)間: 2025-3-28 04:05
MEMS and AI for the Recognition of Human Activities on IoT Platformses or nursing homes. Finally, to determine the position of subjects, we associate the prototype with a positioning system on the ultrasonic platform. Finally, applying the Edge Machine Learning technique, we developed an application on the STM32L475VG microprocessor on which motion acquisition and a作者: 揮舞 時(shí)間: 2025-3-28 08:30
Tackling the?Linear Sum Assignment Problem with?Graph Neural Networksfor a significant increase in classification accuracy if compared with two different DNN approaches based on Dense Networks and Convolutional Neural Networks, furthermore, the GNN has proved to be very efficient with regard to the processing time and memory requirements, thanks to intrinsic paramete作者: 茁壯成長 時(shí)間: 2025-3-28 13:04 作者: HARD 時(shí)間: 2025-3-28 16:04
Optimized Layout: A Genetic Algorithm for Industrial and Business Application that reveal an appreciable robustness and open new scenarios for different applications of the methodology developed in this work, always in the context of optimal management of industrial and commercial spaces.作者: 多嘴多舌 時(shí)間: 2025-3-28 20:31 作者: grovel 時(shí)間: 2025-3-29 02:52 作者: 美麗的寫 時(shí)間: 2025-3-29 04:20
A Novel Fuzzy Semi-supervised Learning Approach for?the?Classification of?Colorectal Cancer (FSSL-CRlassification models such as Support Vector Machine, Random tree, Linear Regression and others, the prediction performance using this strategy on the dataset exhibited remarkable breakthroughs in enhancing the classifier’s results.作者: 惡意 時(shí)間: 2025-3-29 08:06 作者: misshapen 時(shí)間: 2025-3-29 15:04
Identification of?Crown and?Rump in?First-Trimester Ultrasound Images Using Deep Convolutional Neuramodel that implements a pre-trained CNN model, namely, VGG-16. This model is used to classify the segmented images into ‘Good’ and ‘Bad’. Finally, the segmented images are entered into a pre-trained ResNet34 model that identifies the Crown and Rump regions. This can be used by obstetric practitioner作者: nascent 時(shí)間: 2025-3-29 17:24 作者: 多樣 時(shí)間: 2025-3-29 20:25 作者: GIDDY 時(shí)間: 2025-3-30 00:41
https://doi.org/10.1007/978-3-658-26117-7for a significant increase in classification accuracy if compared with two different DNN approaches based on Dense Networks and Convolutional Neural Networks, furthermore, the GNN has proved to be very efficient with regard to the processing time and memory requirements, thanks to intrinsic paramete作者: BAIL 時(shí)間: 2025-3-30 05:48 作者: elucidate 時(shí)間: 2025-3-30 08:29
https://doi.org/10.1007/978-3-319-47892-0 that reveal an appreciable robustness and open new scenarios for different applications of the methodology developed in this work, always in the context of optimal management of industrial and commercial spaces.作者: Prologue 時(shí)間: 2025-3-30 16:03
https://doi.org/10.1007/978-3-319-47892-0andom Forest, XGBoost and Support Vector Machine algorithms were compared to find the best DCE-MRI instant for breast cancer classification: the pre-contrast and the third post-contrast instants resulted as the most informative items. Random Forest can be considered the optimal algorithm showing an 作者: 膠狀 時(shí)間: 2025-3-30 17:40
Rosemond Boohene,Daniel AgyapongG signal and used to build channel.frequency.time volumes. A system based on a custom deep Convolutional Neural Network (CNN), named . was designed and developed to discriminate between pre-hand-opening, pre-hand-closing and resting. The proposed system outperformed a comparable method in the litera作者: RUPT 時(shí)間: 2025-3-30 21:01 作者: LIMN 時(shí)間: 2025-3-31 02:54
Shahamak Rezaei,Victoria Hill,Yipeng Liudel is proposed based on ML models. The proposed ensemble classifier achieved an accuracy of 94.92% which is approximately 5% accuracy increase compared to individual classifier approach. The source code used in this work are publicly available at: 作者: oblique 時(shí)間: 2025-3-31 08:11
Ali Davari,Amer Dehghan Najmabadimodel that implements a pre-trained CNN model, namely, VGG-16. This model is used to classify the segmented images into ‘Good’ and ‘Bad’. Finally, the segmented images are entered into a pre-trained ResNet34 model that identifies the Crown and Rump regions. This can be used by obstetric practitioner作者: ineluctable 時(shí)間: 2025-3-31 09:32 作者: refraction 時(shí)間: 2025-3-31 17:10 作者: Condense 時(shí)間: 2025-3-31 21:16
ConDet2: An Improved Conjunctivitis Detection Portable Healthcare App Powered by Artificial Intelligctivitis. In this work, we present with .ConDet2 which provides an advanced solution than the earlier version of it. It is faster with a higher accuracy level (95%) than the previously released .ConDet.作者: 角斗士 時(shí)間: 2025-4-1 00:59 作者: Macronutrients 時(shí)間: 2025-4-1 03:24
Conference proceedings 2022o Calabria, Italy, during September 1–3, 2022.?.The 38 full papers included in this book were carefully reviewed and selected from 108 submissions. They were organized in topical sections as follows:??Emerging Applications of AI and Informatics;? Application of AI and Informatics in Healthcare; Appl作者: 險(xiǎn)代理人 時(shí)間: 2025-4-1 06:55
1865-0929 d in Reggio Calabria, Italy, during September 1–3, 2022.?.The 38 full papers included in this book were carefully reviewed and selected from 108 submissions. They were organized in topical sections as follows:??Emerging Applications of AI and Informatics;? Application of AI and Informatics in Health
